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biobert_model
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9645
- Accuracy: 0.8711
- F1: 0.8475
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 334 | 0.6463 | 0.6897 | 0.7129 |
| 0.4503 | 2.0 | 668 | 0.3590 | 0.8651 | 0.8269 |
| 0.2715 | 3.0 | 1002 | 0.4549 | 0.8711 | 0.8252 |
| 0.2715 | 4.0 | 1336 | 0.6012 | 0.8681 | 0.8434 |
| 0.1335 | 5.0 | 1670 | 0.6307 | 0.8576 | 0.8313 |
| 0.0746 | 6.0 | 2004 | 0.7658 | 0.8636 | 0.8366 |
| 0.0746 | 7.0 | 2338 | 0.8658 | 0.8666 | 0.8436 |
| 0.0307 | 8.0 | 2672 | 0.8312 | 0.8711 | 0.8453 |
| 0.0148 | 9.0 | 3006 | 0.8922 | 0.8651 | 0.8421 |
| 0.0148 | 10.0 | 3340 | 0.8761 | 0.8726 | 0.8490 |
| 0.0128 | 11.0 | 3674 | 0.9329 | 0.8681 | 0.8462 |
| 0.0105 | 12.0 | 4008 | 0.9512 | 0.8666 | 0.8441 |
| 0.0105 | 13.0 | 4342 | 0.9553 | 0.8711 | 0.8475 |
| 0.0069 | 14.0 | 4676 | 0.9731 | 0.8681 | 0.8445 |
| 0.0046 | 15.0 | 5010 | 0.9645 | 0.8711 | 0.8475 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
